When thinking of farm management topics, many of us think of business operations and production. Information, techniques and tools are often presented as fixed, and focused on measurement, analysis, and data.
For instance, a traditional grain marketing educational program would include topics on contracting options, such as futures, hedge to arrive, basis, and storage and seasonality, but there’s not much there about human behavior and the decision-making process.
While these topics can be quite powerful in operating a farm business and can lead individuals to increased quantitative skills and knowledge, they neglect a key element that could lead to more objectively clear decisions made on merit without excessive bias. This key relates to human behavior.
With clear understanding and application comes recognition and control of individual behaviors and natural filters in thinking that affect each of us, as we work through the decision-making process. Good decision-makers must be able to recognize and understand their own foibles and take measures to nullify potential bias and error in their thinking process to instead make fact-based choices. This valuable skill may be acquired through the study and use of behavioral science concepts, also known as behavioral economics.
Better understanding of the relationship between an individual making a business decision and the challenges and tendencies of making objective choices as a human being encourages improved decision-making that is more aligned with desired outcomes and goals.
By recognizing one’s own thought and behavior patterns, adjustments and compensating actions are made possible. Understanding behavior and its application is a powerful foundation upon which all the other quantitative tools, methods and knowledge may be used. Ultimately, improved ability to make solid decisions and meet your goals will benefit both business and personal endeavors.
It is impossible to capture all the effects of human behavior, including the specifics of when and how farm operational business decisions could or should be made. Each of us is unique, so it is not feasible that applications of behavior economics could be adequately discussed in such a short format.
However, it is also true that there are common behavioral consistencies or drivers among and within each of us. We are, after all, human. This is evidenced in heuristics or “rule-of-thumb strategies” that shorten decision-making time and allow people to function without constantly stopping to think about their next course of action.
Another way to think of heuristic decision-making is like a knee-jerk reaction, shooting from the hip, back of the envelope analysis, etc. In other words, decisions made using generalizations, rules of thumb, common assumptions or incomplete information. This reduces cognitive load such as thinking time and effort, and can be effective for making immediate judgments. However, they often result in irrational or inaccurate conclusions.
The critical point related to the discussion here is that heuristics frequently result in concluding irrationally or inaccurately. As human beings, we tend to want to simplify complexity, conserve time, focus on things we find interesting, and, sometimes, we are forced into situations where quick decisions must be made. As a result of human nature, people tend to naturally create and use heuristic methods, even when we shouldn’t.
6 common biases
A good way to understand how heuristic thinking influences decision outcomes is to discuss some of those common biases and associated examples. Here are six different types of heuristics that may create errors in judgment:
1. Cognitive bias. Psychosocial rehabilitation specialist Kendra Cherry describes this bias as “a systematic error in thinking that occurs when people are processing and interpreting information in the world around them and affects the decisions and judgments that they make.”
It can often be attributed to the use of heuristics. “Heuristics are mental shortcuts that can facilitate problem-solving and probability judgments,” which otherwise would be complex and difficult to navigate. We all use them since complexity requires concentration through repetition and the simplified rule of thumb may work well enough.
An example of such a rule of thumb is the common notion that for each pound of nitrogen that a corn producer adds, an additional bushel will be yielded. While the common assumption may be originally founded on validity, it is largely circumstantial, not entirely accurate, and definitely doesn’t capture the true complexity of the decision to be made.
For instance, it is not true that every pound of nitrogen applied is directly absorbed, used effectively by the plant, or necessarily needed. Does the variety planted have the genetic potential to use the added fertilizer? What is already present in the soil? Furthermore, nitrogen leaching, or atmospheric escape, may cause a loss of nitrogen available to the plant, nitrification of organic matter may or may not occur as expected, and the list goes on.
The point here is that the simple rule of thumb makes it easy to find an answer when, in reality, there are many factors ignored by this assumptive thinking. This does not mean that the rule of thumb is without merit for consideration, but rather, it is important to consider other factors and make needed adjustments to each circumstance.
It is also worth mentioning that over-application of nitrogen fertilizer can have a diminishing effect on yield, meaning that, at some point, the application of nitrogen is costlier than the return from any consequently increased yield.
2. Dunning-Kruger effect. The Dunning-Kruger effect occurs when a person’s lack of knowledge and skills in a given area causes them to overestimate their competence or ability. In contrast, this same effect causes those who excel in a given area to think the task is simple for everyone and underestimate their relative abilities.
For example, a producer who had great success in marketing grain one year faces the challenge of being overconfident in the next year’s marketing season, perhaps believing that their marketing prowess is greater than actuality. This producer may tend to believe they have discovered the key to marketing, without recognizing that there are many contributing factors that are likely to change from year to year.
3. Availability heuristic. This is a tendency to use information that comes to mind quickly and easily when making decisions about the future. To demonstrate, think about the following question: In the U.S., is homicide or stroke a more frequent cause of death? Those who recall instances of homicide, like people who personally know of a homicide victim, viewers of news or crime dramas, are likely to answer homicide.
Conversely, those familiar with stroke victims, or people who personally know of a stroke victim, are more likely to answer stroke. The fact is that the U.S. FBI statistics reported 21,570 deaths by homicide in 2020 versus about 137,000 deaths reported annually due to stroke.
4. Negativity bias. This results in adverse events having a more significant impact on our psychological state than positive events, causing a bias in consequent decisions made. With crop and livestock producers, this would be a natural pitfall since they are exposed to a great deal of risk, weather events, unstable markets, etc.
Decisions are made with more weight placed on the possible negative impact and outcome rather than the true probability of that negative event occurring. One such case would be over-buying unneeded or overly costly insurance policies. A corn producer who experiences a hail event resulting in a crop failure would tend to want to buy more hail insurance than the economic and occurrence probabilities indicate are warranted. The memory of the negative outcome of the hail event could push them to avert a repeated experience at a cost that is much higher than an economically justified price.
5. Gambler’s fallacy. This describes our belief that the probability of a random event occurring in the future is influenced by previous instances of that type of event. For example, a U.S. quarter is flipped five times consecutively and lands showing heads each time. Knowing this, what is the chance that the sixth toss will also land showing heads?
If your response varies from 50% probability, you would be exhibiting the effect of gambler’s fallacy. The key to avoiding this fallacy is to rely on information known to be true; as it is a fair coin with a 50-50 chance of heads, each new toss is independent of the previous toss, meaning that the chance of a sixth toss resulting in heads is 50% probability, nothing more or less.
6. Anchoring bias. This causes us to rely too heavily on the first piece of information we are given about a topic. For instance, during an insurance sales call, the seller may start by quoting a very expensive price for some lavish policy knowing that the buyer is likely to purchase a lower-priced policy.
However, once this higher price is planted in the buyer’s mind, other offered policies may seem like a “good deal,” so that when the buyer purchases a lower-priced policy, they may not recognize its true value, which, when compared to the whole market, is actually overpriced.
There are many more types of biases. Nearly a hundred cognitive-heuristic biases are listed, described and discussed in detail at thedecisionlab.com/biases.
From this discussion, one might believe that heuristic thinking is bad, yet nothing could be further from the truth. At times, these assumptive, quickly made, generalized responses are what keep us safe or even allow us to make good decisions when a heuristic response is appropriate. It is when heuristics and rational thought are properly combined and used, however, that our best decisions are consistently made.
The bottom line is that decision-makers need to beware of biased tendencies and understand when this might be affecting them in a way that results in a less than optimal outcome. The most critical factor in success on any farming or ranching operation is consistently making the best choices possible.
Stockton is a Nebraska Extension agricultural economist.